Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science (Hardcover)

Thomas W. Miller

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商品描述

Master predictive analytics, from start to finish

 

Start with strategy and management

Master methods and build models

Transform your models into highly-effective code—in both Python and R

 

This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math.

 

Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value.

 

Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code.

 

If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more.

 

All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/

 

Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage.

 

Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have.

 

Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data.

 

You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights.

 

You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods.

 

Use Python and R to gain powerful, actionable, profitable insights about:

  • Advertising and promotion
  • Consumer preference and choice
  • Market baskets and related purchases
  • Economic forecasting
  • Operations management
  • Unstructured text and language
  • Customer sentiment
  • Brand and price
  • Sports team performance
  • And much more

 

商品描述(中文翻譯)

從頭到尾掌握預測分析

從策略和管理開始

掌握方法並建立模型

將模型轉化為高效的程式碼 - 包括Python和R

這本獨一無二的書將幫助您使用預測分析、Python和R來解決真實的商業問題並獲得真正的競爭優勢。通過實際案例研究、直觀的數據可視化和最新的Python和R程式碼,您將掌握預測分析的技能,而不需要複雜的數學知識。

逐步進行,您將學習如何定義問題、識別數據、制定和優化模型、撰寫有效的Python和R程式碼、解釋結果等。每一章節都專注於當今預測分析的關鍵應用之一,提供實用技能和知識,讓模型發揮作用並最大化其價值。

Thomas W. Miller是西北大學預測分析先驅計劃的負責人,他涵蓋了您成功所需的一切:策略和管理、方法和模型、技術和程式碼。

如果您對預測分析還不熟悉,您將建立一個準確、可行的基礎。如果您已經在這個領域工作,您將掌握強大的新技能。如果您熟悉Python或R中的任何一種語言,您將發現這些語言彼此互補,使您能夠做更多事情。

所有數據集、廣泛的Python和R程式碼以及其他示例可在http://www.ftpress.com/miller/上下載。

Python和R在預測分析、數據科學和大數據方面具有巨大的威力。這本書將幫助您利用這種威力解決真實的商業問題,並獲得真正的競爭優勢。

Thomas W. Miller獨特的平衡方法結合了商業背景和量化工具,並通過最新版本的Python和R程式碼詳細解釋每一種技術。如果您對預測分析還不熟悉,Miller將為您建立一個準確、可行的基礎。如果您已經是一個模型師、程式設計師或經理,您將學習到關鍵的技能。

使用Python和R,Miller解決了多個商業挑戰,包括分割、品牌定位、產品選擇建模、價格研究、金融、體育、文本分析、情感分析和社交網絡分析。他闡明了橫斷面數據、時間序列、空間和時空數據的使用。

您將了解每個問題的重要性,哪些數據是相關的,以及如何探索您已識別的數據。Miller將引導您通過文字和圖形概念建模每個數據集,然後再次使用實際的程式碼進行建模,以提供可行的見解。

您將學習模型構建、解釋變量子集選擇和驗證,掌握改善外樣本預測性能的最佳實踐。Miller使用數據可視化和統計圖形幫助您探索數據、呈現模型並評估性能。附錄包括fi